scholarly journals Dynamics and Predictability of Hurricane Nadine (2012) Evaluated through Convection-Permitting Ensemble Analysis and Forecasts

2015 ◽  
Vol 143 (11) ◽  
pp. 4514-4532 ◽  
Author(s):  
Erin B. Munsell ◽  
Jason A. Sippel ◽  
Scott A. Braun ◽  
Yonghui Weng ◽  
Fuqing Zhang
Keyword(s):  
Ensemble Kalman Filter ◽  
Regional Scale ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Sensitivity Analyses ◽  
Weather Research And Forecasting ◽  
Sensitivity Experiment ◽  
Steering Flow ◽  
General Success ◽  
Initial Intensity

Abstract The governing dynamics and uncertainties of an ensemble simulation of Hurricane Nadine (2012) are assessed through the use of a regional-scale convection-permitting analysis and forecast system based on the Weather Research and Forecasting (WRF) Model and an ensemble Kalman filter (EnKF). For this case, the data that are utilized were collected during the 2012 phase of the National Aeronautics and Space Administration’s (NASA) Hurricane and Severe Storm Sentinel (HS3) experiment. The majority of the tracks of this ensemble were successful, correctly predicting Nadine’s turn toward the southwest ahead of an approaching midlatitude trough, though 10 members forecasted Nadine to be carried eastward by the trough. Ensemble composite and sensitivity analyses reveal the track divergence to be caused by differences in the environmental steering flow that resulted from uncertainties associated with the position and subsequent strength of a midlatitude trough. Despite the general success of the ensemble track forecasts, the intensity forecasts indicated that Nadine would strengthen, which did not happen. A sensitivity experiment performed with the inclusion of sea surface temperature (SST) updates significantly reduced the intensity errors associated with the simulation. This weakening occurred as a result of cooling of the SST field in the vicinity of Nadine, which led to weaker surface sensible and latent heat fluxes at the air–sea interface. A comparison of environmental variables, including relative humidity, temperature, and shear yielded no obvious differences between the WRF-EnKF simulations and the HS3 observations. However, an initial intensity bias in which the WRF-EnKF vortices are stronger than the observed vortex appears to be the most likely cause of the final intensity errors.

scholarly journals Estimating Daytime Planetary Boundary Layer Heights over a Valley from Rawinsonde Observations at a Nearby Airport: An Application to the Page Valley in Virginia, United States

2016 ◽  
Vol 55 (3) ◽  
pp. 791-809 ◽  
Author(s):  
Temple R. Lee ◽  
Stephan F. J. De Wekker
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Weather Forecasting ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Dispersion Modeling ◽  
Blue Ridge Mountains ◽  
Terrain Following ◽  
Regional Reanalysis

AbstractThe planetary boundary layer (PBL) height is an essential parameter required for many applications, including weather forecasting and dispersion modeling for air quality. Estimates of PBL height are not easily available and often come from twice-daily rawinsonde observations at airports, typically at 0000 and 1200 UTC. Questions often arise regarding the applicability of PBL heights retrieved from these twice-daily observations to surrounding locations. Obtaining this information requires knowledge of the spatial variability of PBL heights. This knowledge is particularly limited in regions with mountainous terrain. The goal of this study is to develop a method for estimating daytime PBL heights in the Page Valley, located in the Blue Ridge Mountains of Virginia. The approach includes using 1) rawinsonde observations from the nearest sounding station [Dulles Airport (IAD)], which is located 90 km northeast of the Page Valley, 2) North American Regional Reanalysis (NARR) output, and 3) simulations with the Weather Research and Forecasting (WRF) Model. When selecting days on which PBL heights from NARR compare well to PBL heights determined from the IAD soundings, it is found that PBL heights are higher (on the order of 200–400 m) over the Page Valley than at IAD and that these differences are typically larger in summer than in winter. WRF simulations indicate that larger sensible heat fluxes and terrain-following characteristics of PBL height both contribute to PBL heights being higher over the Page Valley than at IAD.

scholarly journals CORDEX-WRF v1.3: development of a module for the Weather Research and Forecasting (WRF) model to support the CORDEX community

2019 ◽  
Vol 12 (3) ◽  
pp. 1029-1066 ◽  
Author(s):  
Lluís Fita ◽  
Jan Polcher ◽  
Theodore M. Giannaros ◽  
Torge Lorenz ◽  
Josipa Milovac ◽  
...  
Keyword(s):  
Regional Climate ◽  
Regional Scale ◽  
Wrf Model ◽  
Data Access ◽  
Quality Data ◽  
Weather Research And Forecasting ◽  
Time Step ◽  
Mitigation And Adaptation ◽  
Data Requirements ◽  
Weather Research

Abstract. The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains, and data access and archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent role in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stakeholders and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency and priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time-consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. “Generic” definitions of variables are adopted in order to overcome the model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided into different priority levels following CORDEX specifications (Core, Tier 1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model; for example, the addition of the Core variables slows the model time step by less than a 5 %. The use of the module reduces the requirements of disk storage by about a 50 %. The module performs neither additional statistics over different periods of time nor homogenization of the output data.

scholarly journals Sudden Track Changes of Tropical Cyclones in Monsoon Gyres: Full-Physics, Idealized Numerical Experiments*

2015 ◽  
Vol 72 (4) ◽  
pp. 1307-1322 ◽  
Author(s):  
Jia Liang ◽  
Liguang Wu
Keyword(s):  
Tropical Cyclones ◽  
Numerical Experiments ◽  
Large Scale ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Coalescence Process ◽  
The West ◽  
Steering Flow ◽  
Sharp Turn ◽  
Wind Profiles

Abstract Tropical cyclones (TCs) in the eastern semicircle of large-scale monsoon gyres (MGs) were observed to take either a northward (sudden northward and northward without a sharp turn) or a westward TC turn, but only the northward turn was previously simulated in a barotropic model. To understand what controls TC track types in MGs, idealized numerical experiments are performed using the full-physics Weather Research and Forecasting (WRF) Model. These experiments indicate that TCs initially located in the eastern semicircle of MGs can generally take three types of tracks: a sudden northward track, a westward track, and a northward track without a sharp turn. The track types depend upon the TC movement relative to the MG center. In agreement with barotropic simulations, the WRF simulation confirms that approaching and being collocated with the MG center is crucial to the occurrence of sudden northward TC track changes and that sudden northward track changes can be generally accounted for by changes in the steering flow. TCs that take westward tracks and northward tracks without a sharp turn do not experience such a coalescence process. Westward TCs move faster than MGs and are then located to the west of the MG center, while TCs move more slowly than MGs and then take a northward track without a sharp turn. This study reveals that the specific TC track in the eastern semicircle of an MG is sensitive to the initial wind profiles of both MGs and TCs, suggesting that improvement in the observation of TC and MG structures is very important for predicting TC track types in MGs.

scholarly journals CO2 Transport, Variability, and Budget over the Southern California Air Basin Using the High-Resolution WRF-VPRM Model during the CalNex 2010 Campaign

2018 ◽  
Vol 57 (6) ◽  
pp. 1337-1352 ◽  
Author(s):  
Changhyoun Park ◽  
Christoph Gerbig ◽  
Sally Newman ◽  
Ravan Ahmadov ◽  
Sha Feng ◽  
...  
Keyword(s):  
Los Angeles ◽  
Southern California ◽  
Regional Scale ◽  
Wrf Model ◽  
Net Ecosystem Exchange ◽  
Weather Research And Forecasting ◽  
California Institute Of Technology ◽  
Vegetation Class ◽  
Institute Of Technology ◽  
Photosynthesis And Respiration

AbstractTo study regional-scale carbon dioxide (CO2) transport, temporal variability, and budget over the Southern California Air Basin (SoCAB) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 campaign period, a model that couples the Weather Research and Forecasting (WRF) Model with the Vegetation Photosynthesis and Respiration Model (VPRM) has been used. Our numerical simulations use anthropogenic CO2 emissions of the Hestia Project 2010 fossil-fuel CO2 emissions data products along with optimized VPRM parameters at “FLUXNET” sites, for biospheric CO2 fluxes over SoCAB. The simulated meteorological conditions have been validated with ground and aircraft observations, as well as with background CO2 concentrations from the coastal Palos Verdes site. The model captures the temporal pattern of CO2 concentrations at the ground site at the California Institute of Technology in Pasadena, but it overestimates the magnitude in early daytime. Analysis of CO2 by wind directions reveals the overestimate is due to advection from the south and southwest, where downtown Los Angeles is located. The model also captures the vertical profile of CO2 concentrations along with the flight tracks. The optimized VPRM parameters have significantly improved simulated net ecosystem exchange at each vegetation-class site and thus the regional CO2 budget. The total biospheric contribution ranges approximately from −24% to −20% (daytime) of the total anthropogenic CO2 emissions during the study period.

Intercomparison and Coupling of Ensemble and Four-Dimensional Variational Data Assimilation Methods for the Analysis and Forecasting of Hurricane Karl (2010)

2014 ◽  
Vol 142 (9) ◽  
pp. 3347-3364 ◽  
Author(s):  
Jonathan Poterjoy ◽  
Fuqing Zhang
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Hybrid System ◽  
Ensemble Kalman Filter ◽  
Computational Cost ◽  
Wrf Model ◽  
Variational Data Assimilation ◽  
Weather Research And Forecasting ◽  
Forecast Errors ◽  
Verification Methods

This study examines the performance of ensemble and variational data assimilation systems for the Weather Research and Forecasting (WRF) Model. These methods include an ensemble Kalman filter (EnKF), an incremental four-dimensional variational data assimilation (4DVar) system, and a hybrid system that uses a two-way coupling between the two approaches (E4DVar). The three methods are applied to assimilate routinely collected data and field observations over a 10-day period that spans the life cycle of Hurricane Karl (2010), including the pregenesis disturbance that preceded its development into a tropical cyclone. In general, forecasts from the E4DVar analyses are found to produce smaller 48–72-h forecast errors than the benchmark EnKF and 4DVar methods for all variables and verification methods tested in this study. The improved representation of low- and midlevel moisture and vorticity in the E4DVar analyses leads to more accurate track and intensity predictions by this system. In particular, E4DVar analyses provide persistently more skillful genesis and rapid intensification forecasts than the EnKF and 4DVar methods during cycling. The data assimilation experiments also expose additional benefits of the hybrid system in terms of physical balance, computational cost, and the treatment of asynoptic observations near the beginning of the assimilation window. These factors make it a practical data assimilation method for mesoscale analysis and forecasting, and for tropical cyclone prediction.

scholarly journals Surface representation impacts on turbulent heat fluxes in the Weather Research and Forecasting (WRF) model (v.4.1.3)

2021 ◽  
Vol 14 (6) ◽  
pp. 3939-3967
Author(s):  
Carlos Román-Cascón ◽  
Marie Lothon ◽  
Fabienne Lohou ◽  
Oscar Hartogensis ◽  
Jordi Vila-Guerau de Arellano ◽  
...  
Keyword(s):  
Vegetation Type ◽  
Wrf Model ◽  
Grid Cell ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Surface Representation ◽  
Surface Parameters ◽  
Surface Information ◽  
Mosaic Approach ◽  
Weather Research

Abstract. The water and energy transfers at the interface between the Earth's surface and the atmosphere should be correctly simulated in numerical weather and climate models. This implies the need for a realistic and accurate representation of land cover (LC), including appropriate parameters for each vegetation type. In some cases, the lack of information and crude representation of the surface lead to errors in the simulation of soil and atmospheric variables. This work investigates the ability of the Weather Research and Forecasting (WRF) model to simulate surface heat fluxes in a heterogeneous area of southern France using several possibilities for the surface representation. In the control experiments, we used the default LC database in WRF, which differed significantly from the actual LC. In addition, sub-grid variability was not taken into account since the model uses, by default, only the surface information from the dominant LC category in each pixel (dominant approach). To improve this surface simplification, we designed three new interconnected numerical experiments with three widely used land surface models (LSMs) in WRF. The first one consisted of using a more realistic and higher-resolution LC dataset over the area of analysis. The second experiment aimed at investigating the effect of using a mosaic approach; 30 m sub-grid surface information was used to calculate the final grid fluxes based on weighted averages from values obtained for each LC category. Finally, in the third experiment, we increased the model stomatal conductance for conifer forests due to the large flux errors associated with this vegetation type in some LSMs. The simulations were evaluated with gridded area-averaged fluxes calculated from five tower measurements obtained during the Boundary-Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The results from the experiments differed depending on the LSM and displayed a high dependency of the simulated fluxes on the specific LC definition within the grid cell, an effect that was enhanced with the dominant approach. The simulation of the fluxes improved using the more realistic LC dataset except for the LSMs that included extreme surface parameters for coniferous forest. The mosaic approach produced fluxes more similar to reality and served to particularly improve the latent heat flux simulation of each grid cell. Therefore, our findings stress the need to include an accurate surface representation in the model, including soil and vegetation sub-grid information with updated surface parameters for some vegetation types, as well as seasonal and man-made changes. This will improve the modelled heat fluxes and ultimately yield more realistic atmospheric processes in the model.

scholarly journals The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons

2014 ◽  
Vol 14 (8) ◽  
pp. 2179-2187 ◽  
Author(s):  
T. Haghroosta ◽  
W. R. Ismail ◽  
P. Ghafarian ◽  
S. M. Barekati
Keyword(s):  
Heat Flux ◽  
Wind Speed ◽  
Model Simulation ◽  
Sensible Heat Flux ◽  
Wrf Model ◽  
Heat Fluxes ◽  
Weather Research And Forecasting ◽  
Data Set ◽  
Wind Speed Prediction ◽  
Weather Research

Abstract. The Weather Research and Forecasting (WRF) model includes various configuration options related to physics parameters, which can affect the performance of the model. In this study, numerical experiments were conducted to determine the best combination of physics parameterization schemes for the simulation of sea surface temperatures, latent heat flux, sensible heat flux, precipitation rate, and wind speed that characterized typhoons. Through these experiments, several physics parameterization options within the Weather Research and Forecasting (WRF) model were exhaustively tested for typhoon Noul, which originated in the South China Sea in November 2008. The model domain consisted of one coarse domain and one nested domain. The resolution of the coarse domain was 30 km, and that of the nested domain was 10 km. In this study, model simulation results were compared with the Climate Forecast System Reanalysis (CFSR) data set. Comparisons between predicted and control data were made through the use of standard statistical measurements. The results facilitated the determination of the best combination of options suitable for predicting each physics parameter. Then, the suggested best combinations were examined for seven other typhoons and the solutions were confirmed. Finally, the best combination was compared with other introduced combinations for wind-speed prediction for typhoon Washi in 2011. The contribution of this study is to have attention to the heat fluxes besides the other parameters. The outcomes showed that the suggested combinations are comparable with the ones in the literature.

Characterizing and Optimizing Precipitation Forecasts from a Convection-Permitting Ensemble Initialized by a Mesoscale Ensemble Kalman Filter

2014 ◽  
Vol 29 (6) ◽  
pp. 1295-1318 ◽  
Author(s):  
Craig S. Schwartz ◽  
Glen S. Romine ◽  
Kathryn R. Smith ◽  
Morris L. Weisman
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Initial Conditions ◽  
Characteristic Curve ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Relative Operating Characteristic ◽  
Horizontal Grid ◽  
Grid Length ◽  
Heavy Rainfall Events

Abstract Convection-permitting Weather Research and Forecasting (WRF) Model forecasts with 3-km horizontal grid spacing were produced for a 50-member ensemble over a domain spanning three-quarters of the contiguous United States between 25 May and 25 June 2012. Initial conditions for the 3-km forecasts were provided by a continuously cycling ensemble Kalman filter (EnKF) analysis–forecast system with 15-km horizontal grid length. The 3-km forecasts were evaluated using both probabilistic and deterministic techniques with a focus on hourly precipitation. All 3-km ensemble members overpredicted rainfall and there was insufficient forecast precipitation spread. However, the ensemble demonstrated skill at discriminating between both light and heavy rainfall events, as measured by the area under the relative operating characteristic curve. Subensembles composed of 20–30 members usually demonstrated comparable resolution, reliability, and skill as the full 50-member ensemble. On average, deterministic forecasts initialized from mean EnKF analyses were at least as or more skillful than forecasts initialized from individual ensemble members “closest” to the mean EnKF analyses, and “patched together” forecasts composed of members closest to the ensemble mean during each forecast interval were skillful but came with caveats. The collective results underscore the need to improve convection-permitting ensemble spread and have important implications for optimizing EnKF-initialized forecasts.

scholarly journals Concentric Eyewall Formation in Typhoon Sinlaku (2008). Part I: Assimilation of T-PARC Data Based on the Ensemble Kalman Filter (EnKF)

2012 ◽  
Vol 140 (2) ◽  
pp. 506-527 ◽  
Author(s):  
Chun-Chieh Wu ◽  
Yi-Hsuan Huang ◽  
Guo-Yuan Lien
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
Surface Wind ◽  
Measurement Data ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Secondary Eyewall Formation ◽  
Wind Structure ◽  
The Impact

Typhoon Sinlaku (2008) is a case in point under The Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (T-PARC) with the most abundant flight observations taken and with great potential to address major scientific issues in T-PARC such as structure change, targeted observations, and extratropical transition. A new method for vortex initialization based on ensemble Kalman filter (EnKF) data assimilation and the Weather Research and Forecasting (WRF) model is adopted in this study. By continuously assimilating storm positions (with an update cycle every 30 min), the mean surface wind structure, and all available measurement data, this study constructs a unique high-spatial/temporal-resolution and model/observation-consistent dataset for Sinlaku during a 4-day period. Simulations of Sinlaku starting at different initial times are further investigated to assess the impact of the data. It is striking that some of the simulations are able to capture Sinlaku’s secondary eyewall formation, while others starting the simulation earlier with less data assimilated are not. This dataset provides a unique opportunity to study the dynamical processes of concentric eyewall formation in Sinlaku. In Part I of this work, results from the data assimilation and simulations are presented, including concentric eyewall evolution and the precursors to its formation, while detailed dynamical analyses are conducted in follow-up research.

scholarly journals Impact of Assimilating FY-3D MWTS-2 Upper Air Sounding Data on Forecasting Typhoon Lekima (2019)

2021 ◽  
Vol 13 (9) ◽  
pp. 1841
Author(s):  
Zeyi Niu ◽  
Lei Zhang ◽  
Peiming Dong ◽  
Fuzhong Weng ◽  
Wei Huang
Keyword(s):  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Forecast Performance ◽  
Clear Sky ◽  
Steering Flow ◽  
Microwave Sounding Unit ◽  
Microwave Sounding ◽  
The Mean ◽  
Data Assimilation System ◽  
Statistical Interpolation

In this study, the Fengyun-3D (FY-3D) clear-sky microwave temperature sounder-2 (MWTS-2) radiances were directly assimilated in the regional mesoscale Weather Research and Forecasting (WRF) model using the Gridpoint Statistical Interpolation (GSI) data assimilation system. The assimilation experiments were conducted to compare the track errors of typhoon Lekima from uses of the Advanced Microwave Sounding Unit-A (AMSU-A) radiances (EXP_AD) with those from FY-3D MWTS-2 upper-air sounding data at channels 5–7 (EXP_AMD). The clear-sky mean bias-corrected observation-minus-background (O-B) values of FY-3D MWTS-2 channels 5, 6, and 7 are 0.27, 0.10 and 0.57 K, respectively, which are smaller than those without bias corrections. Compared with the control experiment, which was the forecast of the WRF model without use of satellite data, the assimilation of satellite radiances can improve the forecast performance and reduce the mean track error by 8.7% (~18.4 km) and 30% (~58.6 km) beyond 36 h through the EXP_AD and EXP_AMD, respectively. The direction of simulated steering flow changed from southwest in the EXP_AD to southeast in the EXP_AMD, which can be pivotal to forecasting the landfall of typhoon Lekima (2019) three days in advance. Assimilation of MWTS-2 upper-troposphere channels 5–7 has great potential to improve the track forecasts for typhoon Lekima.

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